人工智能在制药行业的变革力量:提高效率、产品质量和安全性

Mukesh Vijayarangam Rajesh, Karthikeyan Elumalai
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引用次数: 0

摘要

制药行业通过人工智能(AI)实现流程改进、生产力提高和产品质量改进。通过机器学习算法,将大数据和人工智能应用相结合,分析制造效率低下的问题,并对药物配方和包装以及质量控制措施提出改进建议。人工智能将温度调节、压力调节和配料比例控制相结合,可以提高片剂、胶囊和注射剂的生产效率,降低时间要求和成本支出。人工智能还增强了吸塑包装和小瓶包装方法,并自动进行质量控制检查,通过检测缺陷来确保产品的一致性。一致、可靠和有效的生产过程依赖于实时监控和人工智能驱动的调整,这直接有助于提高药品的质量。人工智能对生产过程的持续观察有助于发现与安全相关的风险,包括设备故障和污染风险,同时及时解决这些风险,以保障生产安全。人工智能的利用有助于企业识别必要的设备维护需求,使企业能够在设备发生故障之前组织维护。人工智能驱动的数据洞察使公司能够根据实时数据做出战略选择,自动化操作流程以提高效率,并积极应对新兴的行业模式。通过提高运营效率、减少浪费和提高利润率,人工智能在制药生产中的整合可以改变该行业。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The transformative power of artificial intelligence in pharmaceutical manufacturing: Enhancing efficiency, product quality, and safety
The pharmaceutical manufacturing industry transforms through artificial intelligence (AI) by implementing process improvements along with productivity enhancements and product quality improvements. The combination of big data and AI applications through machine learning algorithms analyzes manufacturing inefficiencies and recommends improvements for both medicine formulation and packaging as well as quality control measures. The combination of temperature adjustment, pressure adjustment, and ingredient proportion control enables AI to enhance the production efficiency of tablets, capsules, and injections, and decrease both time requirements and cost expenses. AI also enhances blister pack and vial packing methods and automates quality control inspections to ensure consistency of products by detecting defects. Consistent, reliable, and effective production processes rely on real-time monitoring and AI-driven adjustments, which directly contribute to manufacturing pharmaceutical products of improved quality. The continuous observation of the production process by AI helps to detect safety-related risks, including equipment failures and contamination risks, while addressing them promptly to preserve production security. The utilization of AI helps businesses identify necessary equipment maintenance demands which enables companies to organize maintenance before equipment breakdowns occur. AI-driven data insights enable companies to make strategic choices based on real-time data, automate operational processes for efficiency, and respond to emerging industry patterns positively. Through enhanced operational efficiency, waste minimization, and improvement of profit margins, AI integration in pharmaceutical production can transform the sector.
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